code: def reproduce_fitting_error(
      pipeline_id: str,
      base_path=None,
      use_input_preprocessing: bool = True,
  ):
      from fedot.core.pipelines.pipeline import Pipeline
  
      if not base_path:
          base_path = Path(default_fedot_data_dir(), "debug_info")
  
      pipeline = Pipeline(
          use_input_preprocessing=use_input_preprocessing
      )
      pipeline.load(
          str(
              Path(
                  base_path,
                  f"{pipeline_id}_pipeline",
                  f"{pipeline_id}_pipeline.json",
              )
          )
      )
      with open(
          Path(base_path, f"{pipeline_id}_train_data.pkl"), "rb"
      ) as file:
          train_data = pickle.load(file)
      with open(
          Path(base_path, f"{pipeline_id}_test_data.pkl"), "rb"
      ) as file:
          test_data = pickle.load(file)
      pipeline.unfit()
      pipeline.fit(train_data)
      pipeline.predict(test_data)
  
file_path: FEDOT/fedot/utilities/debug.py
imports: import os
  import pickle
  from pathlib import Path
  from typing import TYPE_CHECKING
  from uuid import uuid4
  from fedot.core.utils import default_fedot_data_dir
label_desc: Use image node_id 4 for calling a global function with example usage: reproduce_fitting_error(pipeline_id, base_path, use_input_preprocessing) without return types